1. Field of the Invention
The present invention relates to a camcorder, and more particularly, to a motion compensating apparatus and method for stabilizing vibrations due to an operator's shaking hands during video photography.
2. Description of the Related Art
The ability to detect a motion vector from a moving picture signal is a basic requirement for picture compression, picture recognition and picture stability. In particular, when an image is photographed using a VCR-incorporated camera (hereinafter, a camcorder) while walking or riding in a vehicle, for example, an unstable image is likely to be input to the camcorder due to camera vibration caused by the operator's shaking hands. This instability or vibration is an even greater factor when photographing at increased magnification, such as when conducting video photography using a zoom feature.
Thus, in order to correctly compensate for the vibration due to hand shaking, the motion vectors should be detected at the subpixel level as well as at the pixel level. However, such a detection scheme increases the number of operations required and also requires that a complicated interpolating circuit be incorporated in the camcorder. Further, as the picture magnification increases, the probability also increases that stray motion information will be detected which is unrelated to the hand shaking.
A conventional method for compensating for hand shaking motion will be described with reference to FIG. 1 and FIG. 2.
In the motion vector detecting method shown in FIG. 1, image formation for an entire image or a partial image of a picture is input in step 10. In step 12, the most recently inputted image formation is compared with image information that was previously inputted, either by field or frame, to detect horizontal and vertical motion vectors to be optimized. When the motion vectors are detected using the information for the entire image, an abundance of pattern information within the image can be used in an attempt to correctly detect the horizontal and vertical motion vectors. However, there is a limit to resolving the components of the motion, especially when using partial image information.
In step 14, an image in a field memory is compensated using the detected horizontal and vertical motion vectors. Thereafter, the image is enlarged by a predetermined magnification ratio in step 16.
While the motion compensating method shown in FIG. 1 can stably compensate for the motion in most cases, it cannot always correctly detect the specific motion vectors to be compensated, thereby resulting in erroneous motion compensation.
FIG. 2 illustrates another conventional motion compensating method. As before, the entire or partial image information of a picture is first input in step 20. In step 22, the input image is electronically magnified in order to more accurately detect the motion components of the image. In step 24, the horizontal and vertical motion vectors V.sub.x and V.sub.y of the magnified image are detected through the following formulas (1) and (2): ##EQU1##
In the above formulas (1) and (2) `P` is a value obtained by projecting a luminance component of an image in the first dimension, which represents the first dimensional pattern information of the image; `Corr` denotes a correlation value between a current projection value `P.sup.n ` and a past projection value `P.sup.n-1 `; `W` and `H` denote a width and a height of the image, respectively; `x` denotes a pixel in a horizontal direction; and `y` denotes a pixel in a vertical direction.
The amount of optimized motion of an image is estimated to the horizontal and vertical positions where the correlation value is the minimum. At this time, the unit of the output motion vector is an integer value. In order to realize a more accurate motion vector, the correlation value is interpolated to find the most optimized (minimum) value at the pixel level. Likewise, at the subpixel level, the values `P.sup.n ` and `P.sup.n-1 ` are interpolated to find the most optimized correlation value.
In step 26, after the horizontal and vertical motion vectors V.sub.x and V.sub.y are detected, an image in a field memory is compensated using these vectors.
Note that in step 22, the amount of extracted and magnified image motion information should be sufficiently large in order to correctly detect the motion vectors at the subpixel level. However, since the motion information of the image is inversely proportional to the magnification ratio of the electrically magnified image, there is a limit to securing stability of the motion vectors. In particular, when many independent motions exist at the magnified portion of the image, the motions of an object in the image are compensated, but the image motions due to the hand shaking are not. Therefore, the target for stability frequently changes between the entire image and the object in the image, thereby greatly lowering the stability of the image.